Evidence map›Paper›PMID 29058599›Full record

ArticleGenome biology2017

Evidence of reduced recombination rate in human regulatory domains.

Yaping Liu, Abhishek Sarkar, Pouya Kheradpour, Jason Ernst, Manolis Kellis

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

38 citing papers in PubMed, 1 synthesis or guideline pooled it, 58 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Yaping LiuComputer Science and Artificial Intelligence Lab (CSAIL), Massachusetts Institute of Technology, Massachusetts, USA.
Abhishek SarkarComputer Science and Artificial Intelligence Lab (CSAIL), Massachusetts Institute of Technology, Massachusetts, USA.
Pouya KheradpourComputer Science and Artificial Intelligence Lab (CSAIL), Massachusetts Institute of Technology, Massachusetts, USA.
Jason ErnstDepartment of Biological Chemistry, David Geffen School of Medicine, University of California at Los Angeles, California, USA.
Manolis KellisComputer Science and Artificial Intelligence Lab (CSAIL), Massachusetts Institute of Technology, Massachusetts, USA. manoli@mit.edu.
Broad Institute · USMassachusetts Institute of Technology · USUniversity of California, Los Angeles · US

Funding

Epigenomic variation atlas across human tissues and individuals in GTExU01HG007610 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI KELLIS, MANOLIS · 2014 to 2016
$3.0M
Comparative analysis and regulatory architecture of epigenomics datasetsR01GM113708 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI KELLIS, MANOLIS · 2015 to 2017
$852k
NHGRI NIH HHS U01 HG007610NIGMS NIH HHS R01 GM113708
6 · The paper itself

Abstract

backgroundRecombination rate is non-uniformly distributed across the human genome. The variation of recombination rate at both fine and large scales cannot be fully explained by DNA sequences alone. Epigenetic factors, particularly DNA methylation, have recently been proposed to influence the variation in recombination rate.

resultsWe study the relationship between recombination rate and gene regulatory domains, defined by a gene and its linked control elements. We define these links using expression quantitative trait loci (eQTLs), methylation quantitative trait loci (meQTLs), chromatin conformation from publicly available datasets (Hi-C and ChIA-PET), and correlated activity links that we infer across cell types. Each link type shows a "recombination rate valley" of significantly reduced recombination rate compared to matched control regions. This recombination rate valley is most pronounced for gene regulatory domains of early embryonic development genes, housekeeping genes, and constitutive regulatory elements, which are known to show increased evolutionary constraint across species. Recombination rate valleys show increased DNA methylation, reduced doublestranded break initiation, and increased repair efficiency, specifically in the lineage leading to the germ line. Moreover, by using only the overlap of functional links and DNA methylation in germ cells, we are able to predict the recombination rate with high accuracy.

conclusionsOur results suggest the existence of a recombination rate valley at regulatory domains and provide a potential molecular mechanism to interpret the interplay between genetic and epigenetic variations.

Indexed as

DNA MethylationRecombination, GeneticRegulatory Sequences, Nucleic AcidAnimalsChromosomes, HumanDNA Breaks, Double-StrandedEmbryonic DevelopmentGene ExpressionGenes, EssentialHumansMiceQuantitative Trait LociDNA methylationRecombination rateRegulatory domain

Identifiers

PMID29058599
PMCPMC5651596
OpenAlexW2766412303

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.